Linking Distributed Optimization Models for Food, Water, and Energy Security Nexus Management

Yuri Ermoliev,Tatiana Ermolieva,Elena Rovenskaya,Petr Havlik,Vjacheslav L Bogdanov,Anatolij G Zagorodny,Nadejda Komendantova,Michael Obersteiner

doi:10.3390/su14031255

Abstract

Traditional integrated modeling (IM) is based on developing and aggregating all relevant (sub)models and data into a single integrated linear programming (LP) model. Unfortunately, this approach is not applicable for IM under asymmetric information (ASI), i.e., when “private” information regarding sectoral/regional models is not available, or it cannot be shared by modeling teams (sectoral agencies). The lack of common information about LP submodels makes LP methods inapplicable for integrated LP modeling. The aim of this paper is to develop a new approach to link and optimize distributed sectoral/regional optimization models, providing a means of decentralized cross-sectoral coordination in the situation of ASI. Thus, the linkage methodology enables the investigation of policies in interdependent systems in a “decentralized” fashion. For linkage, the sectoral/regional models do not need recoding or reprogramming. They also do not require additional data harmonization tasks. Instead, they solve their LP submodels independently and in parallel by a specific iterative subgradient algorithm for nonsmooth optimization. The submodels continue to be the same separate LP models. A social planner (regulatory agency) only needs to adjust the joint resource constraints to simple subgradient changes calculated by the algorithm. The approach enables more stable and resilient systems’ performance and resource allocation as compared to the independent policies designed by separate models without accounting for interdependencies. The paper illustrates the application of the methodology to link detailed energy and agricultural production planning models under joint constraints on water and land use.

Highlights

Introduction iationsThe increasing interdependencies among food-energy-water-environmental (FEWE)sectors require integrated coherent planning and coordinated policies for sustainable development and security nexus
The resource quotas for each system and each resource are recalculated by systems independently and in parallel via shifting their each resource are recalculated by systems independently and in parallel via shifting their current approximation the direction defined the corresponding dual variables from current approximation inin the direction defined byby the corresponding dual variables from the primal sectoral optimization problem
The approach allows to avoid hard linking of the models in a single code that saves programming time and enables parallel linking of the models in a single code that saves programming time and enables parallel distributed computations of sectoral models instead of a large-scale integrated model, i.e., distributed computations of sectoral models instead of a large-scale integrated model, i.e., addressing the well-known “curse of dimensionality” and large-scale data harmonization addressing the well-known “curse of dimensionality” and large-scale data harmonization. This preserves the original models in their initial state for other. This preserves the original models in their initial state for other pospossible linkages

Summary

Introduction

Sectors require integrated coherent planning and coordinated policies for sustainable development and security nexus. The sectors become more interconnected because they utilize common, often rather limited, resources, both natural (e.g., land, water, air quality) and socio-economic (e.g., investments, labor force). Land and water are needed for agricultural production and for hydropower generation, coal mining and processing, power plants cooling, renewable energy, and hydrogen production. The energy sector is one of the largest and fast-growing water consumers. The more water is used by the energy sector, the more vulnerable energy production and production in other water-dependent sectors, becomes [1]. Climate change concerns and rapid energy sector transition towards renewable energy sources tighten the links between energy and Licensee MDPI, Basel, Switzerland

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